Adaptive Intelligence

This capstone project developed two concept directions for more human-centered interactions with emerging technology, focusing on how people can feel supported without feeling monitored or overwhelmed. The work framed everyday experiences as a balance between capability, clarity, and control.

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The first concept, AI Guardian, imagines a proactive assistant that helps people anticipate needs, make decisions, and stay safe across daily life. It centers trust as a primary design requirement, emphasizing transparency, user approval for meaningful actions, and privacy-by-design so support feels helpful rather than intrusive.

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The second concept, Variable Tech UI, explores adaptable interfaces that can shift how advanced functionality is presented based on a person’s preferences and the situation. The goal is to reduce cognitive load by right-sizing complexity, offering interaction modes that fit the moment, and making sophisticated features feel intuitive instead of demanding.

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Across both concepts, research and synthesis pointed to three consistent themes: adoption depends on trust and clear user control, personalization is valuable only when it stays lightweight, and systems should reduce mental effort through context-aware, flexible interaction. These learnings shaped how each concept defines autonomy, permissions, and the role of user choice.

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Together, the concepts propose a roadmap from vision to validation: test scenarios with target users using lightweight prototypes, define a concrete trust and control model for data and actions, and build a narrow end-to-end MVP slice for each concept to evaluate usability, perceived value, and feasibility with real workflows.